public class AdditiveRegression extends IteratedSingleClassifierEnhancer implements OptionHandler, AdditionalMeasureProducer, WeightedInstancesHandler, TechnicalInformationHandler, IterativeClassifier
@techreport{Friedman1999,
author = {J.H. Friedman},
institution = {Stanford University},
title = {Stochastic Gradient Boosting},
year = {1999},
PS = {http://www-stat.stanford.edu/\~jhf/ftp/stobst.ps}
}
Valid options are:
-S Specify shrinkage rate. (default = 1.0, ie. no shrinkage)
-I <num> Number of iterations. (default 10)
-D If set, classifier is run in debug mode and may output additional info to the console
-W Full name of base classifier. (default: weka.classifiers.trees.DecisionStump)
Options specific to classifier weka.classifiers.trees.DecisionStump:
-D If set, classifier is run in debug mode and may output additional info to the console
NUM_DECIMAL_PLACES_DEFAULT| Constructor and Description |
|---|
AdditiveRegression()
Default constructor specifying DecisionStump as the classifier
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AdditiveRegression(Classifier classifier)
Constructor which takes base classifier as argument.
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| Modifier and Type | Method and Description |
|---|---|
void |
buildClassifier(Instances data)
Method used to build the classifier.
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double |
classifyInstance(Instance inst)
Classify an instance.
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void |
done()
Clean up.
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java.util.Enumeration<java.lang.String> |
enumerateMeasures()
Returns an enumeration of the additional measure names
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Capabilities |
getCapabilities()
Returns default capabilities of the classifier.
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double |
getMeasure(java.lang.String additionalMeasureName)
Returns the value of the named measure
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java.lang.String[] |
getOptions()
Gets the current settings of the Classifier.
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java.lang.String |
getRevision()
Returns the revision string.
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double |
getShrinkage()
Get the shrinkage rate.
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TechnicalInformation |
getTechnicalInformation()
Returns an instance of a TechnicalInformation object, containing
detailed information about the technical background of this class,
e.g., paper reference or book this class is based on.
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java.lang.String |
globalInfo()
Returns a string describing this attribute evaluator
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void |
initializeClassifier(Instances data)
Initialize classifier.
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java.util.Enumeration<Option> |
listOptions()
Returns an enumeration describing the available options.
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static void |
main(java.lang.String[] argv)
Main method for testing this class.
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double |
measureNumIterations()
return the number of iterations (base classifiers) completed
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boolean |
next()
Perform another iteration.
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void |
setOptions(java.lang.String[] options)
Parses a given list of options.
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void |
setShrinkage(double l)
Set the shrinkage parameter
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java.lang.String |
shrinkageTipText()
Returns the tip text for this property
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java.lang.String |
toString()
Returns textual description of the classifier.
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getNumIterations, numIterationsTipText, setNumIterationsclassifierTipText, getClassifier, setClassifierbatchSizeTipText, debugTipText, distributionForInstance, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, implementsMoreEfficientBatchPrediction, makeCopies, makeCopy, numDecimalPlacesTipText, runClassifier, setBatchSize, setDebug, setDoNotCheckCapabilities, setNumDecimalPlacesequals, getClass, hashCode, notify, notifyAll, wait, wait, waitdistributionForInstancepublic AdditiveRegression()
public AdditiveRegression(Classifier classifier)
classifier - the base classifier to usepublic java.lang.String globalInfo()
public TechnicalInformation getTechnicalInformation()
getTechnicalInformation in interface TechnicalInformationHandlerpublic java.util.Enumeration<Option> listOptions()
listOptions in interface OptionHandlerlistOptions in class IteratedSingleClassifierEnhancerpublic void setOptions(java.lang.String[] options)
throws java.lang.Exception
-S Specify shrinkage rate. (default = 1.0, ie. no shrinkage)
-I <num> Number of iterations. (default 10)
-D If set, classifier is run in debug mode and may output additional info to the console
-W Full name of base classifier. (default: weka.classifiers.trees.DecisionStump)
Options specific to classifier weka.classifiers.trees.DecisionStump:
-D If set, classifier is run in debug mode and may output additional info to the console
setOptions in interface OptionHandlersetOptions in class IteratedSingleClassifierEnhanceroptions - the list of options as an array of stringsjava.lang.Exception - if an option is not supportedpublic java.lang.String[] getOptions()
getOptions in interface OptionHandlergetOptions in class IteratedSingleClassifierEnhancerpublic java.lang.String shrinkageTipText()
public void setShrinkage(double l)
l - the shrinkage rate.public double getShrinkage()
public Capabilities getCapabilities()
getCapabilities in interface ClassifiergetCapabilities in interface CapabilitiesHandlergetCapabilities in class SingleClassifierEnhancerCapabilitiespublic void buildClassifier(Instances data) throws java.lang.Exception
buildClassifier in interface ClassifierbuildClassifier in class IteratedSingleClassifierEnhancerdata - the training data to be used for generating the
bagged classifier.java.lang.Exception - if the classifier could not be built successfullypublic void initializeClassifier(Instances data) throws java.lang.Exception
initializeClassifier in interface IterativeClassifierdata - the training datajava.lang.Exception - if the classifier could not be initialized successfullypublic boolean next()
throws java.lang.Exception
next in interface IterativeClassifierjava.lang.Exception - if this iteration fails for unexpected reasonspublic void done()
done in interface IterativeClassifierpublic double classifyInstance(Instance inst) throws java.lang.Exception
classifyInstance in interface ClassifierclassifyInstance in class AbstractClassifierinst - the instance to predictjava.lang.Exception - if an error occurspublic java.util.Enumeration<java.lang.String> enumerateMeasures()
enumerateMeasures in interface AdditionalMeasureProducerpublic double getMeasure(java.lang.String additionalMeasureName)
getMeasure in interface AdditionalMeasureProduceradditionalMeasureName - the name of the measure to query for its valuejava.lang.IllegalArgumentException - if the named measure is not supportedpublic double measureNumIterations()
public java.lang.String toString()
toString in class java.lang.Objectpublic java.lang.String getRevision()
getRevision in interface RevisionHandlergetRevision in class AbstractClassifierpublic static void main(java.lang.String[] argv)
argv - should contain the following arguments:
-t training file [-T test file] [-c class index]